Triple

T24955032
Position Surface form Disambiguated ID Type / Status
Subject Muhlenberg Township, Pennsylvania E624448 entity
Predicate river P165 FINISHED
Object Maiden Creek
Maiden Creek is a tributary of the Schuylkill River in eastern Pennsylvania, known for flowing through Berks County and providing recreational opportunities and water resources to nearby communities.
E2289208 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Maiden Creek | Statement: [Muhlenberg Township, Pennsylvania, river, Maiden Creek]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Maiden Creek
Triple: [Muhlenberg Township, Pennsylvania, river, Maiden Creek]
Generated description
Maiden Creek is a tributary of the Schuylkill River in eastern Pennsylvania, known for flowing through Berks County and providing recreational opportunities and water resources to nearby communities.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e2ff23a3a88190b1b9743fe5e15f94 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f4240331848190a8419adaed32360e completed May 1, 2026, 3:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5b131bbc248190bb67c58dfc7f9e19 completed July 18, 2026, 5:46 a.m.
NEDg Description generation batch_6a5b13be2ab08190b3eb06d07aa270a5 completed July 18, 2026, 5:48 a.m.
NED2 Entity disambiguation (via description) batch_6a5b13e1e2e081908507247f2e913b90 completed July 18, 2026, 5:49 a.m.
Created at: April 18, 2026, 5:57 a.m.